Chen, WeiTran, Hong T.Liang, ZhiyongLin, HaoZhang, Liqing2019-01-252019-01-252015-09-072045-232213859http://hdl.handle.net/10919/86891Knowledge of the distribution of N-6-methyladenosine (m(6)A) is invaluable for understanding RNA biological functions. However, limitation in experimental methods impedes the progress towards the identification of m(6)A site. As a complement of experimental methods, a support vector machine based-method is proposed to identify m(6)A sites in Saccharomyces cerevisiae genome. In this model, RNA sequences are encoded by their nucleotide chemical property and accumulated nucleotide frequency information. It is observed in the jackknife test that the accuracy achieved by the proposed model in identifying the m(6)A site was 78.15%. For the convenience of experimental scientists, a webserver for the proposed model is provided at http://lin.uestc.edu.cn/server/m6Apred.php.8application/pdfen-USCreative Commons Attribution 4.0 Internationalmessenger-rnapredictionrevealsrecognitionm(6)a-seqresiduessitesArticle - Refereedhttps://doi.org/10.1038/srep13859526343792